Development of computer vision algorithms for tissue identification and segmentation in medical ultrasound images

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Ultrasound is one of the more patient friendly medical imaging modalities. It is the modality of choice for infants as the equipment can be brought to the bassinette or incubator and administered with minimal disturbance or side effects to the infant. Similarly the equipment can easily be brought to adult patients and the procedure is well tolerated by the extremely ill. However, ultrasound images contain speckle and noise making the extraction of diagnostic information from these images more challenging than for other imaging modalities. The goal of this research project is to develop automated software tools that will help the physician extract relevant diagnostic information from these ultrasound images. In particular to develop an automated technique for the identification and characterization of tissue types so that ultimately healthy tissue can be reliably distinguished from unhealthy tissue. Improving the viability of using a more patient friendly imaging modality while still achieving the same or better clinical results will have a significant impact on patient health and health care costs.